使用生理学测量来确定认知工作量:瞳孔测量和心率变化
Xinyue Ma1, Radmehr Monfared1, Rebecca Grant1
1School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Leicestershire LE11 3TU, UK.
Sensors (Basel, Switzerland)
|March 28, 2024
概括
这项研究引入了一种新的方法来测量工业4.0制造业中的认知工作负载,使用心率变化和瞳孔计等生理信号来评估操作员的表现和幸福感. 这些发现支持优化以人为中心的数字化工作场所.
科学领域:
- 人与计算机的交互
- 工业工程 工业工程 工业工程
- 认知科学 认知科学
背景情况:
- 工业4.0的采用需要了解数字化制造业中的操作员福利和认知工作负载.
- 现有的认知工作量测量方法可能不足以适应新的数字技术.
- 需要一种新的方法来准确评估心理工作量及其对绩效的影响.
研究的目的:
- 提出和验证一种新的方法来确定以人为中心的制造环境中的认知工作负载指数.
- 建立任务复杂性,认知工作量,专业知识和操作员表现之间的关系.
- 加强数字化工作场所的设计和优化.
主要方法:
- 17名操作人员使用眼睛跟踪和心电图传感器捕获了生理信号 (心率变化,瞳孔测量).
- 操作人员在不同复杂度的万克尔发动机块上执行组装任务.
- 数据分析的重点是开发和验证基于生物标记物的认知负载指数.
主要成果:
- 在不同任务复杂度级别 (休息,低,中,高) 中观察到认知负载指数的统计学上显著差异.
- 与现有的指标相比,开发的指标对任务复杂性的变化具有更高的灵敏度.
- 初步发现表明,专家可能会经历较低的认知负载,需要进一步调查.
结论:
- 拟议的方法利用兼容的心脏和瞳孔测量生物标记物,有效地测量认知工作负载.
- 这种方法对于设计和优化以人为中心的制造环境是有价值的.
- 准确的认知负载评估对于在工业4.0中保持操作员健康和性能至关重要.
相关概念视频
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